Characterisation of source and reservoir rocks is important for evaluation of both conventional and unconventional reservoirs. In addition to inorganic matter, organic matter is deposited and preserved at the bottom of lakes, seas and deltas. As more material is deposited, the organic matter is buried and the heat and pressure of burial transforms the organic matter into geopolymers such as kerogen and bitumen. When the rocks containing organic matter are buried deep enough, the rocks undergo catagenesis, where temperature begins to convert the kerogen into bitumen and ultimately into hydrocarbons such as oil and gas. The rocks that produce hydrocarbons are referred to as source rocks.
Kerogen and bitumen are large organic molecules of no fixed structure. The composition of the kerogen and bitumen depends both on the type of organic matter used to produce them and the thermal maturity of the sample. While kerogen and bitumen have different molecular structures, they are typically separated functionally; the latter is soluble in common organic solvents while the former is not. The majority of bitumen is produced later during catagenesis, though a small amount occurs from diagenesis.
Understanding kerogen and bitumen properties and content is important for estimation of thermal maturity and potential hydrocarbon production. Thermal maturity indicates how much and what type of hydrocarbon is expected to be produced from an unconventional shale reservoir or a conventional reservoir sourced by a particular or multiple source rocks. In addition to kerogen and bitumen, a third class of organic matter, pyrobitumen, may exist in more thermally mature systems. Like kerogen, pyrobitumen is also insoluble in typical organic solvents. However, while kerogen originates from the originally deposited organic matter, the pyrobitumen comes from the cracking of bitumen during catagenesis and metagenesis.
The current standard method for determining thermal maturity is programmed pyrolysis, such as the “Rock-Eval™” (Vinci Technologies) or “Source Rock Analysis” techniques. These will heat up a crushed portion of sample in an oven or ovens in a series of stages at different temperatures to pyrolyse and oxidize the sample. The “Rock-Eval™” analyser, for example, includes a flame ionization detector (FID) that measures organic compound gases released during each stage of heating while sensitive infrared detectors are used to measure the quantity of CO and CO2 generated during pyrolysis and oxidation of samples. A thermocouple monitors temperatures, which are recorded on a chart known as a pyrogram. The measured organic compound gases, CO and CO2 are plotted as a function of temperature on the pyrogram. During the first heating stage, the sample is held at an initial temperature for a period of time and the produced products are measured. This is referred to as the S1 peak, which relates to the hydrocarbons and bitumen in the sample. The temperature is then ramped higher. A second peak, S2, corresponds to the hydrocarbons that evolve from the sample during the second programmed heating stage of pyrolysis, which result from the thermal cracking of kerogen. The associated release of carbon dioxide (CO2) and carbon monoxide (CO) during pyrolysis is measured by the IR detector. The S3 peak corresponds to the amount of CO and CO2 that is evolved from thermal cracking of the kerogen during pyrolysis. This peak is associated with the organic associated oxygen in the sample. The temperature at which the S2 peak has the highest signal intensity, and thus maximum generation of hydrocarbons from kerogen, is referred to as Tmax. Tmax relates to thermal maturity, as higher temperatures are required to crack the kerogen into hydrocarbons for more thermally mature samples. There is the potential to heat the sample up to even higher temperatures and observe the produced products. For example, the high temperature programmed pyrolysis can be used to measure the Spy peak, which relates to pyrobitumen.
The programmed pyrolysis methods are bulk methods; the samples need to be crushed and homogenized before measurement. Therefore, any spatial information regarding the distribution of organic matter is lost during the crushing process. They are also, practically, completely destructive with respect to the samples, as the samples cannot be used for further tests after programmed pyrolysis. Programmed pyrolysis measurements are time intensive, usually requiring about an hour per sample to perform. The results also can have issues with interference from carbonate in the sample. If the samples are carbonate rich, they typically will need to be pretreated with hydrochloric acid to prevent interference in the measurement.
Thermal maturity is often estimated using the temperature where the maximum number of hydrocarbon products are produced from kerogen. This can be unreliable, as the Tmax peaks are often quite broad, such that the exact location of the peak can vary and can be difficult to reproduce with subsequent measurements. Thermal maturity calculations from Tmax are often unreliable particularly for low organic content samples. As programmed pyrolysis methods take approximately an hour per sample, this is a time intensive method to measure thermal maturity.
The standard method for obtaining mineralogical information is X-Ray diffraction (XRD). XRD works by irradiating samples with monochromatic x-rays, which are scattered at characteristic angles by crystalline materials. Amorphous materials, e.g. organic matter, contain no long term order and therefore will not produce peaks at characteristic angles. By observing the peak heights and location from a sample, the mineralogy of the sample can be estimated. This method is time consuming, requiring roughly half an hour measurement time depending on operation parameters. If clay speciation is required, the samples need to be treated with chemicals such as ethylene glycol and heated overnight, adding to the total time required. Furthermore, XRD peaks are commonly assessed manually, which can lead to subjectivity and significant variation of results between operators.
Laser induced breakdown spectroscopy (LIBS) uses a laser to ablate a tiny portion of sample. The standard for LIBS uses a q-switched solid state laser that produces a rapid pulse, typically on the order of pico- to nanoseconds in duration. Optics are used to focus the energy onto a single spot on the sample and the laser is used to ablate a small portion of sample, creating a high temperature plasma. The excited atoms of the plasma then return to a ground state, giving off light at characteristic frequencies associated with different elements. The spot size vaporized by the laser can range in size from a few microns up to hundreds of microns, allowing a large range of resolution and is dependent on the optics of the system. The signal quality improves with larger spot size, but sacrifices resolution. While a small amount of sample is consumed, the amount is so small that it is considered to be negligible and the technique is considered non-destructive. The wavelength of light from the plasma can be in the 180 to 980 nm region. Detection means may comprise a spectrometer adjusted to a part of the spectral region. The resulting spectra can be analysed by multivariate data analysis to correlate the spectra to concentration of elements. The spectroscopic analysis of the optical emission in LIBS is different from analytical approaches based on mass spectrometry.
LIBS has been used as a method for mineralogy identification, making it an alternative to X-ray Diffraction (XRD) and X-ray Fluorescence (XRF) methods for mineralogical analysis of samples. It has an advantage over XRF for mineralogical identification because it can measure all elements, whereas XRF is unable to detect light elements. LIBS does have a disadvantage in terms of quantification of heavier elements compared to XRF.
LIBS has also been used previously to act as a rapid pyrolysis method to obtain TOC and geochemical parameters. The laser is used to both ablate material for measurement and to volatize organic material. By monitoring the changes in elements between laser shots, the rate and amount of loss of elements associated with organic matter (e.g. H, C) can be used to predict the geochemical properties of a sample.
Laser Induced Pyrolysis (LIPS) methods have been used previously on geological samples. LIPS relies on mass-spectroscopy methods of detecting and analysing the products of pyrolysis instead of optical emissions spectroscopy. Further, those LIPS methods appear to be limited to just total organic carbon (TOC), and do not appear to present information on thermal maturity or kerogen versus bitumen discrimination nor mineralogy.
Fourier transform infrared spectroscopy (FTIR) works by shining infrared light upon a sample and determining the wavelengths of light absorbed by the sample. The infrared region of the electromagnetic spectrum ranges from 700 nm to 1 mm and is broken up into the sub regions of: near infrared (0.7 to 1.4 μm), short wavelength infrared (1.4 to 3 μm), mid wavelength infrared (3 to 8 μm), long wavelength infrared (8 to 15 μm), and far-infrared (15 to 1000 μm). Molecular bonds in the sample have vibrational modes, (e.g. symmetrical and antisymmetrical stretching, rocking, wagging, scissoring, etc.) that can be excited by application of light at the same frequency as the vibrational mode. When the sample is irradiated with IR light, depending on the composition of the sample, some wavelengths of the light will be absorbed while others will pass through the sample. The transmitted light is then measured to produce a spectra showing the absorption profile as a function of wavelength. Organic matter and inorganic minerals have characteristic absorption profiles which can be used to identify sample constituents. This may be done qualitatively or quantitatively by use of mineral libraries, manual identification, univariate analysis or multivariate analysis. FTIR can be performed via transmission FTIR, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), or attenuated total reflectance (ATR) FTIR.
Fourier Transform Infrared spectroscopy has been used to estimate both mineralogy and geochemical parameters. The exact minerals predicted varies between models, but typically consists of 5-10 different mineral species that are predicted. Analysis of the FTIR spectrum with multivariate analysis has shown good predictive value for geochemical parameters such as TOC, S1, S2, and to a lesser degree S3. Predictive ability of FTIR to date for hydrogen and oxygen indices and Tmax, however, has been of poor quality. Normal FTIR suffers the same drawback of loss of spatial resolution of the mineralogy and organic matter as XRD and programmed pyrolysis, as samples need to be powdered before measurement.
Fourier transform infrared (FTIR) microscopy combines FTIR measurements with spatial resolution to produce a FTIR spectrum. The FTIR microscope advances normal FTIR measurements by combining the technique with an optical microscope such that individual areas of a sample can be selected and FTIR spectra taken, allowing composition at a higher resolution to be determined. Unlike standard FTIR measurements which are normally performed on powders, the FTIR microscopy can be performed on intact samples. Standard procedure for geological FTIR microscopy uses a sample that is polished to produce an even surface. FTIR microscopy can be performed via transmission FTIR, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), attenuated total reflectance (ATR) FTIR or photoacoustic FTIR spectroscopy.
Raman spectroscopy uses monochromatic light, usually from a laser, to excite rotational and vibrational modes in a sample. Raman spectroscopy measures the Raman scattering, the inelastic scattering that occurs when light interacts with matter. When photons from the laser interact with the molecular vibrations in the sample, they change the excitation state of the molecule. As the molecule returns to equilibrium, this results in the emission of an inelastically scattered photon that may be of higher or lower frequency than the excitation depending on whether the final vibration state of the molecule is higher or lower than the original state. These shifts give information on the vibrational and rotational modes of the sample, which can be related to its material composition. The signal to noise of Raman spectroscopy tends to be weaker compared to other methods such as FTIR.
Hyperspectral imaging creates a spectra for each pixel of an image. Light from an object passes through a dispersing element, such as a prism or a diffraction grating, and then travels to a detector. Optics are typically used in between the dispersing element and the detector to improve image quality and resolution. Hyperspectral imaging may range over a wide range of light wavelengths, including both visible and non-visible light. Multispectral is a subset of hyperspectral imaging that focuses on a few wavelengths of key interest. Hyperspectral imaging is defined by measuring narrow, well defined contiguous wavelengths. Multispectral imaging instead has broad resolution or the wavelengths to be measured are not adjacent to each other. Hyperspectral imaging has been used previously in a wide range of industries. In particular, hyperspectral imaging has been used in aerial mounted surveys to determine mineralogy for oil, gas, and mineral exploration.
Vibrational spectroscopy has the advantage that it is generally robust in prediction for larger categories of sample characterization (e.g. clays, carbonates. etc.), but often encounters problems in distinguishing subspecies. For example, carbonates such as calcite, dolomite, ankerite and siderite all have very similar FTIR absorption spectra. Clays also tend to have spectra that are similar to one another. Other minerals, like pyrite, lack a distinct FTIR spectrum, making prediction difficult of these minerals.
While LIBS works well to characterise samples similar to those used in the calibration set, it can encounter problems when trying to characterise samples in formations different than those used for calibration. Elements can belong to a wide variety of samples constituents and the elemental variations in minerals that occur in natural samples can make prediction on new samples challenging. In addition, samples of differing mineralogical structure may have similar elemental composition, which can make prediction more uncertain.
In the FTIR spectrum, the organic signal occurs as aliphatic and aromatic peaks. The aliphatic peaks in the spectra are usually well defined but the aromatic peaks overlap in the region of the spectra where the carbonate peaks occur. If there is a significant quantity of carbonate present, this makes it more difficult to distinguish the aromatic peaks. Multivariate methods such as partial least squares can be used to still predict organic content, but the results are more uncertain for more thermally mature samples, which predominantly have aromatic organic matter. Raman spectroscopy has problems with fluorescence from organic content that can interfere with spectral measurement of the samples.
With LIBS, while the hydrogen and carbon content of the organic matter is known, this ratio can vary with both the thermal maturity of the sample and the kerogen type, therefore making prediction of organic content and thermal maturity more uncertain.
Previous work has been done to combine Raman spectroscopy and LIBS measurements for development work for Mars Rover missions. These measurements have not been performed on petroleum source or reservoir rocks, but focused on rocks expected to be similar to those found on Mars, e.g., igneous materials.